Geographic gazetteer

Describe, retrieve and prepare dataframes with geographic boundaries of various geographic units of the USA.

Source files

Source data files are downloaded from web and cached locally.

Census Bureau: - TIGER Data Products Guide: Which Product Should I Use? - Cartographic Boundary Files. 2018 and before, 2019 and after. Simplified representations of selected geographic areas from the Census Bureau’s MAF/TIGER geographic database. Small scale (limited detail) spatial files clipped to shoreline. - TIGER/Line shapefiles. Most comprehensive geographic dataset in full detail. - Relationship files. These text files describe geographic relationships. There are two types of relationship files; those that show the relationship between the same type of geography over time (comparability) and those that show the relationship between two types of geography for the same time period. - LSAD codes. Legal/Statistical Area Description Codes and Definitions - FIPS codes - Gazeteer reference files - Character encoding. Files from 2014 and earlier use “ISO-8859-1”, 2015 and after use “UTF-8”.

Shapefile format

Wikipedia

Census Bureau shapefiles come as zipped folders and can be read directly with geopandas.

XML metadata

Most zipped shapefile folders contain XML documents with metadata. Helper functions here parse these files for inspection. In later years files ending with .iso.xml adhere to ISO standards and can be more easily parsed for feature descriptions.

Scale

Shapefiles are available in different scale. TIGER is the most precise, then follows 1:500,000, then 1:5,000,000, and 1:20,000,000 is the lowest resolution.

Shapefile revisions change from year to year. Between year differences are clearly visible in all scales except TIGER.

Table below compares boundaries of Tolland County, Connecticut, taken from shapefiles in different years and scales. “Length” column is is boundary length in shape units (degrees), and “points” is the total number of points in the polygon.

scale	length	points
tiger 2010	1.877432	2152
tiger 2020	1.877094	2097
500k 2010	1.852025	201
500k 2020	1.854092	236
5m 2010	1.767873	50
20m 2010	1.623553	27

Map below visualizes boundary differences.

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States

CODE	ABBR	NAME	ALAND	AWATER
01	AL	Alabama	131174048583	4593327154
02	AK	Alaska	1478839695958	245481577452
04	AZ	Arizona	294198551143	1027337603
05	AR	Arkansas	134768872727	2962859592
06	CA	California	403503931312	20463871877
08	CO	Colorado	268422891711	1181621593
09	CT	Connecticut	12542497068	1815617571
10	DE	Delaware	5045925646	1399985648
11	DC	District of Columbia	158340391	18687198
12	FL	Florida	138949136250	31361101223
13	GA	Georgia	149482048342	4422936154
15	HI	Hawaii	16633990195	11777809026
16	ID	Idaho	214049787659	2391722557
17	IL	Illinois	143780567633	6214824948
18	IN	Indiana	92789302676	1538002829
19	IA	Iowa	144661267977	1084180812
20	KS	Kansas	211755344060	1344141205
21	KY	Kentucky	102279490672	2375337755
22	LA	Louisiana	111897594374	23753621895
23	ME	Maine	79887426037	11746549764
24	MD	Maryland	25151100280	6979966958
25	MA	Massachusetts	20205125364	7129925486
26	MI	Michigan	146600952990	103885855702
27	MN	Minnesota	206228939448	18945217189
28	MS	Mississippi	121533519481	3926919758
29	MO	Missouri	178050802184	2489425460
30	MT	Montana	376962738765	3869208832
31	NE	Nebraska	198956658395	1371829134
32	NV	Nevada	284329506470	2047206072
33	NH	New Hampshire	23189413166	1026675248
34	NJ	New Jersey	19047825980	3544860246
35	NM	New Mexico	314196306401	728776523
36	NY	New York	122049149763	19246994695
37	NC	North Carolina	125923656064	13466071395
38	ND	North Dakota	178707534813	4403267548
39	OH	Ohio	105828882568	10268850702
40	OK	Oklahoma	177662925723	3374587997
41	OR	Oregon	248606993270	6192386935
42	PA	Pennsylvania	115884442321	3394589990
72	PR	Puerto Rico	8868896030	4922382562
44	RI	Rhode Island	2677779902	1323670487
45	SC	South Carolina	77864918488	5075218778
46	SD	South Dakota	196346981786	3382720225
47	TN	Tennessee	106802728188	2350123465
48	TX	Texas	676653171537	19006305260
49	UT	Utah	212886221680	6998824394
50	VT	Vermont	23874175944	1030416650
51	VA	Virginia	102257717110	8528531774
53	WA	Washington	172112588220	12559278850
54	WV	West Virginia	62266474513	489028543
55	WI	Wisconsin	140290039723	29344951758
56	WY	Wyoming	251458544898	1867670745

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Counties

Source data

Cartographic Boundary Files are available for 1990, 2000, 2010, 2013 and every year after that.

TIGER/Line Shapefiles in shapefile format are available for 2000, 2007 and every year after that. 1992 and 2006 are available in legacy format.

Changes

County changes happen whenever decided by local authoritities. Annually released boundary files reflect boundaries effective January 1 of the reference year. List of changes here.

Substantial county boundary changes are those affecting an estimated population of 200 or more; changes of at least one square mile where an estimated population number was not available, but research indicated that 200 or more people may have been affected; and annexations of unpopulated territory of at least 10 square miles.

CRS in 1990 and 2000 is unknown, created dataframes have “naive geometries”.

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Census Tracts

Code is 11 digits: 2 state, 5 county, 4+2 tract.

Reference

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Changes over time

Major changes to tract codes and shapes change after decennial censuses, with smaller changes in between years.

The first four digits of the tract code are “permanent.” When tracks get large (+8000 residents), tracts are split and 2 digit tag is used (same with the split of splits):

1990	2000	2010
1000	1000.01	1000.03
1000	1000.01	1000.04
1000	1000.02	1000.05
1000	1000.02	1000.06

The naming convention for merges (population falls below 1,200) and boundary revisions are less clear-cut.

When changes (splits, merges, redefinitions) occur, the relationship of new tracts to old tracts is crosswalked.

There is a master file, as well as two files that provided the identifiers of tracts that were “substantially changed” between decennials. The two files of significantly changed census tracts consist only of a list of census tracts that exhibited a change of 2.5-percent or greater. Tract relationships may be one-to-one, many-to-one, one-to-many, or many-to-many.

Relationship files are currently available for 2010 (relative to 2000) and 2000 (relative to 1990).

• 2010: data, metadata.
• 2000: data, metadata.

Split

All tracts in \(y_1\) are a partition of a single tract in \(y_0\).

Join

All tracts in \(y_0\) are a partition of a single tract in \(y_1\).

Other reshape

Arbitrary change in boundaries between two or more adjacent tracts. May include multiple splits, joins and boundary shifts.

ZIP Code Tabulation Area (ZCTA)

Homepage

ZIP Code Tabulation Areas (ZCTAs) are generalized areal representations of United States Postal Service (USPS) ZIP Code service areas. The USPS ZIP Codes identify the individual post office or metropolitan area delivery station associated with mailing addresses. USPS ZIP Codes are not areal features but a collection of mail delivery routes.

ZCTAs are build from census block, thus blocks can be used as cross-walk to other geographics that partition into blocks. Relationship files are available for blocks, counties, county subdivisions, places, tracts, and for ZCTA changes over time.

Cartographic boundary and TIGER shapefiles. 2000 files are only 3-digit codes. For some reason, the 2010 CB file is almost x10 bigger than other years - 527mb.

ZCTA shapefile columns over time

	2000	2010	2013	2014	2015	2016	2017	2018	2019	2020
AREA	X
PERIMETER	X
Z399_D00_	X
Z399_D00_I	X
ZCTA3	X
NAME	X	X
LSAD	X	X
LSAD_TRANS	X
geometry	X	X	X	X	X	X	X	X	X	X
GEO_ID		X
ZCTA5		X
CENSUSAREA		X
ZCTA5CE10			X	X	X	X	X	X	X
AFFGEOID10			X	X	X	X	X	X	X
GEOID10			X	X	X	X	X	X	X
ALAND10			X	X	X	X	X	X	X
AWATER10			X	X	X	X	X	X	X
ZCTA5CE20										X
AFFGEOID20										X
GEOID20										X
NAME20										X
LSAD20										X
ALAND20										X
AWATER20										X

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Figure 1: ZCTAs in Dane county, WI from 2013 and 2020 revisions.

Congressional Districts

A geographical and political division in which voters elect representatives to the U.S. House of Representatives. Each state establishes its congressional districts based on population counts, with the goal of having districts as equal in population as possible. (ESRI dictionary)

About Congressional Districts (Census) - All congressional districts population are supposed to be equal throughout the state to equally be able to elect the representative - They don’t cross state lines, but may cross all other classifications such as Census tracts. - They DO cross county boundaries - Map of CT for reference - Closer breakdown of District 1 in CT - States are required to redraw the district lines every 10 years after the Census is released (except single district states)

In 33 states, state legislatures play the dominant role in congressional redistricting. In eight states, commissions draw congressional district lines. In two states, hybrid systems are used, in which the legislatures share redistricting authority with commissions. The remaining states comprise one congressional district each, rendering redistricting unnecessary (AK, DE, DC, MT, ND, SD, VT, WY). Link

Gerrymandering can and often does occur with congressional districts lines to help whomever the in power party is to make them stay in power. Examples

School Districts

The U.S. has more than 13,000 geographically defined public school districts. These include districts that are administratively and fiscally independent of any other government, as well as public school systems that lack sufficient autonomy to be counted as separate governments and are classified as a dependent agency of some other government—a county, municipal, township, or state. Most public school systems are Unified districts that operate regular, special, and/or vocational programs for children in Prekindergarten through 12th grade.

• School districts are complex and have almost no consistency from state to state because they are formulated by the local town government in most public school cases.
• Boundary files
• Since they vary by local government then changes happen every year in many places throughout the US.

Native American Reservations

About | Definitions | Data

Diffrent breakdowns are avalible, going as small as tracts and block groups (link).

Build this module

Converted notebook "nbs/geography.ipynb" to module "rurec/geography.py".